import pytest import numpy as np from scipy import stats from damask import Rotation from damask import Table from damask import _rotation from damask import grid_filters from damask import tensor n = 1000 atol=1.e-4 @pytest.fixture def res_path(res_path_base): """Directory containing testing resources.""" return res_path_base/'Rotation' @pytest.fixture def set_of_rotations(set_of_quaternions): return [Rotation.from_quaternion(s) for s in set_of_quaternions] @pytest.fixture def multidim_rotations(set_of_quaternions): L = len(set_of_quaternions) i = 0 while L%(f:=np.random.randint(2,np.sqrt(L).astype(int))) > 0 and i 1.e-8: s = np.sign(qu[0])/np.sqrt(qu[1]**2+qu[2]**2+qu[3]**2) omega = 2.0 * np.arccos(np.clip(qu[0],-1.0,1.0)) ax = ax = np.array([ qu[1]*s, qu[2]*s, qu[3]*s, omega ]) else: ax = ax = np.array([ qu[1], qu[2], qu[3], np.pi]) return ax def qu2ro(qu): """Quaternion to Rodrigues-Frank vector.""" if iszero(qu[0]): ro = np.array([qu[1], qu[2], qu[3], np.inf]) else: s = np.linalg.norm(qu[1:4]) ro = np.array([0.0,0.0,_P,0.0] if iszero(s) else \ [ qu[1]/s, qu[2]/s, qu[3]/s, np.tan(np.arccos(np.clip(qu[0],-1.0,1.0)))]) return ro def qu2ho(qu): """Quaternion to homochoric vector.""" omega = 2.0 * np.arccos(np.clip(qu[0],-1.0,1.0)) if np.abs(omega) < 1.0e-12: ho = np.zeros(3) else: ho = np.array([qu[1], qu[2], qu[3]]) f = 0.75 * ( omega - np.sin(omega) ) ho = ho/np.linalg.norm(ho) * f**(1./3.) return ho #---------- Rotation matrix ---------- def om2qu(om): trace = om.trace() if trace > 0: s = 0.5 / np.sqrt(trace+ 1.0) qu = np.array([0.25 / s,( om[2,1] - om[1,2] ) * s,( om[0,2] - om[2,0] ) * s,( om[1,0] - om[0,1] ) * s]) else: if ( om[0,0] > om[1,1] and om[0,0] > om[2,2] ): s = 2.0 * np.sqrt( 1.0 + om[0,0] - om[1,1] - om[2,2]) qu = np.array([ (om[2,1] - om[1,2]) / s,0.25 * s,(om[0,1] + om[1,0]) / s,(om[0,2] + om[2,0]) / s]) elif (om[1,1] > om[2,2]): s = 2.0 * np.sqrt( 1.0 + om[1,1] - om[0,0] - om[2,2]) qu = np.array([ (om[0,2] - om[2,0]) / s,(om[0,1] + om[1,0]) / s,0.25 * s,(om[1,2] + om[2,1]) / s]) else: s = 2.0 * np.sqrt( 1.0 + om[2,2] - om[0,0] - om[1,1] ) qu = np.array([ (om[1,0] - om[0,1]) / s,(om[0,2] + om[2,0]) / s,(om[1,2] + om[2,1]) / s,0.25 * s]) if qu[0]<0: qu*=-1 return qu*np.array([1.,_P,_P,_P]) def om2eu(om): """Rotation matrix to Bunge-Euler angles.""" if not np.isclose(np.abs(om[2,2]),1.0,0.0): zeta = 1.0/np.sqrt(1.0-om[2,2]**2) eu = np.array([np.arctan2(om[2,0]*zeta,-om[2,1]*zeta), np.arccos(om[2,2]), np.arctan2(om[0,2]*zeta, om[1,2]*zeta)]) else: eu = np.array([np.arctan2( om[0,1],om[0,0]), np.pi*0.5*(1-om[2,2]),0.0]) # following the paper, not the reference implementation eu[np.abs(eu)<1.e-8] = 0.0 eu = np.where(eu<0, (eu+2.0*np.pi)%np.array([2.0*np.pi,np.pi,2.0*np.pi]),eu) return eu def om2ax(om): """Rotation matrix to axis angle pair.""" ax=np.empty(4) # first get the rotation angle t = 0.5*(om.trace() -1.0) ax[3] = np.arccos(np.clip(t,-1.0,1.0)) if np.abs(ax[3])<1.e-8: ax = np.array([ 0.0, 0.0, 1.0, 0.0]) else: w,vr = np.linalg.eig(om) # next, find the eigenvalue (1,0j) i = np.where(np.isclose(w,1.0+0.0j))[0][0] ax[0:3] = np.real(vr[0:3,i]) diagDelta = -_P*np.array([om[1,2]-om[2,1],om[2,0]-om[0,2],om[0,1]-om[1,0]]) ax[0:3] = np.where(np.abs(diagDelta)<1e-12, ax[0:3],np.abs(ax[0:3])*np.sign(diagDelta)) return ax #---------- Bunge-Euler angles ---------- def eu2qu(eu): """Bunge-Euler angles to quaternion.""" ee = 0.5*eu cPhi = np.cos(ee[1]) sPhi = np.sin(ee[1]) qu = np.array([ cPhi*np.cos(ee[0]+ee[2]), -_P*sPhi*np.cos(ee[0]-ee[2]), -_P*sPhi*np.sin(ee[0]-ee[2]), -_P*cPhi*np.sin(ee[0]+ee[2]) ]) if qu[0] < 0.0: qu*=-1 return qu def eu2om(eu): """Bunge-Euler angles to rotation matrix.""" c = np.cos(eu) s = np.sin(eu) om = np.array([[+c[0]*c[2]-s[0]*s[2]*c[1], +s[0]*c[2]+c[0]*s[2]*c[1], +s[2]*s[1]], [-c[0]*s[2]-s[0]*c[2]*c[1], -s[0]*s[2]+c[0]*c[2]*c[1], +c[2]*s[1]], [+s[0]*s[1], -c[0]*s[1], +c[1] ]]) om[np.abs(om)<1.e-12] = 0.0 return om def eu2ax(eu): """Bunge-Euler angles to axis angle pair.""" t = np.tan(eu[1]*0.5) sigma = 0.5*(eu[0]+eu[2]) delta = 0.5*(eu[0]-eu[2]) tau = np.linalg.norm([t,np.sin(sigma)]) alpha = np.pi if iszero(np.cos(sigma)) else \ 2.0*np.arctan(tau/np.cos(sigma)) if np.abs(alpha)<1.e-6: ax = np.array([ 0.0, 0.0, 1.0, 0.0 ]) else: ax = -_P/tau * np.array([ t*np.cos(delta), t*np.sin(delta), np.sin(sigma) ]) # passive axis angle pair so a minus sign in front ax = np.append(ax,alpha) if alpha < 0.0: ax *= -1.0 # ensure alpha is positive return ax def eu2ro(eu): """Bunge-Euler angles to Rodrigues-Frank vector.""" ro = eu2ax(eu) # convert to axis angle pair representation if ro[3] >= np.pi: # Differs from original implementation. check convention 5 ro[3] = np.inf elif iszero(ro[3]): ro = np.array([ 0.0, 0.0, _P, 0.0 ]) else: ro[3] = np.tan(ro[3]*0.5) return ro #---------- Axis angle pair ---------- def ax2qu(ax): """Axis angle pair to quaternion.""" if np.abs(ax[3])<1.e-6: qu = np.array([ 1.0, 0.0, 0.0, 0.0 ]) else: c = np.cos(ax[3]*0.5) s = np.sin(ax[3]*0.5) qu = np.array([ c, ax[0]*s, ax[1]*s, ax[2]*s ]) return qu def ax2om(ax): """Axis angle pair to rotation matrix.""" c = np.cos(ax[3]) s = np.sin(ax[3]) omc = 1.0-c om=np.diag(ax[0:3]**2*omc + c) for idx in [[0,1,2],[1,2,0],[2,0,1]]: q = omc*ax[idx[0]] * ax[idx[1]] om[idx[0],idx[1]] = q + s*ax[idx[2]] om[idx[1],idx[0]] = q - s*ax[idx[2]] return om if _P < 0.0 else om.T def ax2ro(ax): """Axis angle pair to Rodrigues-Frank vector.""" if np.abs(ax[3])<1.e-6: ro = [ 0.0, 0.0, _P, 0.0 ] else: ro = [ax[0], ax[1], ax[2]] # 180 degree case ro += [np.inf] if np.isclose(ax[3],np.pi,atol=1.0e-15,rtol=0.0) else \ [np.tan(ax[3]*0.5)] ro = np.array(ro) return ro def ax2ho(ax): """Axis angle pair to homochoric vector.""" f = (0.75 * ( ax[3] - np.sin(ax[3]) ))**(1.0/3.0) ho = ax[0:3] * f return ho #---------- Rodrigues-Frank vector ---------- def ro2ax(ro): """Rodrigues-Frank vector to axis angle pair.""" if np.abs(ro[3]) < 1.e-8: ax = np.array([ 0.0, 0.0, 1.0, 0.0 ]) elif not np.isfinite(ro[3]): ax = np.array([ ro[0], ro[1], ro[2], np.pi ]) else: angle = 2.0*np.arctan(ro[3]) ta = np.linalg.norm(ro[0:3]) ax = np.array([ ro[0]*ta, ro[1]*ta, ro[2]*ta, angle ]) return ax def ro2ho(ro): """Rodrigues-Frank vector to homochoric vector.""" if np.sum(ro[0:3]**2.0) < 1.e-8: ho = np.zeros(3) else: f = 2.0*np.arctan(ro[3]) -np.sin(2.0*np.arctan(ro[3])) if np.isfinite(ro[3]) else np.pi ho = ro[0:3] * (0.75*f)**(1.0/3.0) return ho #---------- Homochoric vector---------- def ho2ax(ho): """Homochoric vector to axis angle pair.""" tfit = np.array([+0.9999999999999968, -0.49999999999986866, -0.025000000000632055, -0.003928571496460683, -0.0008164666077062752, -0.00019411896443261646, -0.00004985822229871769, -0.000014164962366386031, -1.9000248160936107e-6, -5.72184549898506e-6, +7.772149920658778e-6, -0.00001053483452909705, +9.528014229335313e-6, -5.660288876265125e-6, +1.2844901692764126e-6, +1.1255185726258763e-6, -1.3834391419956455e-6, +7.513691751164847e-7, -2.401996891720091e-7, +4.386887017466388e-8, -3.5917775353564864e-9]) # normalize h and store the magnitude hmag_squared = np.sum(ho**2.) if iszero(hmag_squared): ax = np.array([ 0.0, 0.0, 1.0, 0.0 ]) else: hm = np.ones_like(hmag_squared) # convert the magnitude to the rotation angle s = 0.0 for t in tfit: s += t * hm hm *= hmag_squared ax = np.append(ho/np.sqrt(hmag_squared),2.0*np.arccos(np.clip(s,-1.0,1.0))) return ax def ho2cu(ho): """ Homochoric vector to cubochoric vector. References ---------- D. Roşca et al., Modelling and Simulation in Materials Science and Engineering 22:075013, 2014 https://doi.org/10.1088/0965-0393/22/7/075013 """ rs = np.linalg.norm(ho) if np.allclose(ho,0.0,rtol=0.0,atol=1.0e-16): cu = np.zeros(3) else: xyz3 = ho[_get_pyramid_order(ho,'forward')] # inverse M_3 xyz2 = xyz3[0:2] * np.sqrt( 2.0*rs/(rs+np.abs(xyz3[2])) ) # inverse M_2 qxy = np.sum(xyz2**2) if np.isclose(qxy,0.0,rtol=0.0,atol=1.0e-16): Tinv = np.zeros(2) else: q2 = qxy + np.max(np.abs(xyz2))**2 sq2 = np.sqrt(q2) q = (_beta/np.sqrt(2.0)/_R1) * np.sqrt(q2*qxy/(q2-np.max(np.abs(xyz2))*sq2)) tt = np.clip((np.min(np.abs(xyz2))**2+np.max(np.abs(xyz2))*sq2)/np.sqrt(2.0)/qxy,-1.0,1.0) Tinv = np.array([1.0,np.arccos(tt)/np.pi*12.0]) if np.abs(xyz2[1]) <= np.abs(xyz2[0]) else \ np.array([np.arccos(tt)/np.pi*12.0,1.0]) Tinv = q * np.where(xyz2<0.0,-Tinv,Tinv) # inverse M_1 cu = np.array([ Tinv[0], Tinv[1], (-1.0 if xyz3[2] < 0.0 else 1.0) * rs / np.sqrt(6.0/np.pi) ]) /_sc cu = cu[_get_pyramid_order(ho,'backward')] return cu #---------- Cubochoric ---------- def cu2ho(cu): """ Cubochoric vector to homochoric vector. References ---------- D. Roşca et al., Modelling and Simulation in Materials Science and Engineering 22:075013, 2014 https://doi.org/10.1088/0965-0393/22/7/075013 """ # transform to the sphere grid via the curved square, and intercept the zero point if np.allclose(cu,0.0,rtol=0.0,atol=1.0e-16): ho = np.zeros(3) else: # get pyramide and scale by grid parameter ratio XYZ = cu[_get_pyramid_order(cu,'forward')] * _sc # intercept all the points along the z-axis if np.allclose(XYZ[0:2],0.0,rtol=0.0,atol=1.0e-16): ho = np.array([0.0, 0.0, np.sqrt(6.0/np.pi) * XYZ[2]]) else: order = [1,0] if np.abs(XYZ[1]) <= np.abs(XYZ[0]) else [0,1] q = np.pi/12.0 * XYZ[order[0]]/XYZ[order[1]] c = np.cos(q) s = np.sin(q) q = _R1*2.0**0.25/_beta * XYZ[order[1]] / np.sqrt(np.sqrt(2.0)-c) T = np.array([ (np.sqrt(2.0)*c - 1.0), np.sqrt(2.0) * s]) * q # transform to sphere grid (inverse Lambert) # note that there is no need to worry about dividing by zero, since XYZ[2] can not become zero c = np.sum(T**2) s = c * np.pi/24.0 /XYZ[2]**2 c = c * np.sqrt(np.pi/24.0)/XYZ[2] q = np.sqrt( 1.0 - s ) ho = np.array([ T[order[1]] * q, T[order[0]] * q, np.sqrt(6.0/np.pi) * XYZ[2] - c ]) ho = ho[_get_pyramid_order(cu,'backward')] return ho def _get_pyramid_order(xyz,direction=None): """ Get order of the coordinates. Depending on the pyramid in which the point is located, the order need to be adjusted. Parameters ---------- xyz : numpy.ndarray coordinates of a point on a uniform refinable grid on a ball or in a uniform refinable cubical grid. References ---------- D. Roşca et al., Modelling and Simulation in Materials Science and Engineering 22:075013, 2014 https://doi.org/10.1088/0965-0393/22/7/075013 """ order = {'forward':np.array([[0,1,2],[1,2,0],[2,0,1]]), 'backward':np.array([[0,1,2],[2,0,1],[1,2,0]])} if np.maximum(abs(xyz[0]),abs(xyz[1])) <= xyz[2] or \ np.maximum(abs(xyz[0]),abs(xyz[1])) <=-xyz[2]: p = 0 elif np.maximum(abs(xyz[1]),abs(xyz[2])) <= xyz[0] or \ np.maximum(abs(xyz[1]),abs(xyz[2])) <=-xyz[0]: p = 1 elif np.maximum(abs(xyz[2]),abs(xyz[0])) <= xyz[1] or \ np.maximum(abs(xyz[2]),abs(xyz[0])) <=-xyz[1]: p = 2 return order[direction][p] #################################################################################################### #################################################################################################### def mul(me, other): """ Multiplication. Parameters ---------- other : numpy.ndarray or Rotation Vector, second or fourth order tensor, or rotation object that is rotated. """ if me.quaternion.shape != (4,): raise NotImplementedError('Support for multiple rotations missing') if isinstance(other, Rotation): me_q = me.quaternion[0] me_p = me.quaternion[1:] other_q = other.quaternion[0] other_p = other.quaternion[1:] R = me.__class__(np.append(me_q*other_q - np.dot(me_p,other_p), me_q*other_p + other_q*me_p + _P * np.cross(me_p,other_p))) return R._standardize() elif isinstance(other, np.ndarray): if other.shape == (3,): A = me.quaternion[0]**2.0 - np.dot(me.quaternion[1:],me.quaternion[1:]) B = 2.0 * np.dot(me.quaternion[1:],other) C = 2.0 * _P * me.quaternion[0] return A*other + B*me.quaternion[1:] + C * np.cross(me.quaternion[1:],other) elif other.shape == (3,3,): R = me.as_matrix() return np.dot(R,np.dot(other,R.T)) elif other.shape == (3,3,3,3,): R = me.as_matrix() return np.einsum('ia,jb,kc,ld,abcd->ijkl',R,R,R,R,other) RR = np.outer(R, R) RRRR = np.outer(RR, RR).reshape(4 * (3,3)) axes = ((0, 2, 4, 6), (0, 1, 2, 3)) return np.tensordot(RRRR, other, axes) else: raise ValueError('Can only rotate vectors, 2nd order tensors, and 4th order tensors') else: raise TypeError(f'Cannot rotate {type(other)}') class TestRotation: @pytest.mark.parametrize('forward,backward',[(Rotation._qu2om,Rotation._om2qu), (Rotation._qu2eu,Rotation._eu2qu), (Rotation._qu2ax,Rotation._ax2qu), (Rotation._qu2ro,Rotation._ro2qu), (Rotation._qu2ho,Rotation._ho2qu), (Rotation._qu2cu,Rotation._cu2qu)]) def test_quaternion_internal(self,set_of_rotations,forward,backward): """Ensure invariance of conversion from quaternion and back.""" for rot in set_of_rotations: m = rot.as_quaternion() o = backward(forward(m)) ok = np.allclose(m,o,atol=atol) if np.isclose(rot.as_quaternion()[0],0.0,atol=atol): ok |= np.allclose(m*-1.,o,atol=atol) assert ok and np.isclose(np.linalg.norm(o),1.0), f'{m},{o},{rot.as_quaternion()}' @pytest.mark.parametrize('forward,backward',[(Rotation._om2qu,Rotation._qu2om), (Rotation._om2eu,Rotation._eu2om), (Rotation._om2ax,Rotation._ax2om), (Rotation._om2ro,Rotation._ro2om), (Rotation._om2ho,Rotation._ho2om), (Rotation._om2cu,Rotation._cu2om)]) def test_matrix_internal(self,set_of_rotations,forward,backward): """Ensure invariance of conversion from rotation matrix and back.""" for rot in set_of_rotations: m = rot.as_matrix() o = backward(forward(m)) ok = np.allclose(m,o,atol=atol) assert ok and np.isclose(np.linalg.det(o),1.0), f'{m},{o},{rot.as_quaternion()}' @pytest.mark.parametrize('forward,backward',[(Rotation._eu2qu,Rotation._qu2eu), (Rotation._eu2om,Rotation._om2eu), (Rotation._eu2ax,Rotation._ax2eu), (Rotation._eu2ro,Rotation._ro2eu), (Rotation._eu2ho,Rotation._ho2eu), (Rotation._eu2cu,Rotation._cu2eu)]) def test_Eulers_internal(self,set_of_rotations,forward,backward): """Ensure invariance of conversion from Euler angles and back.""" for rot in set_of_rotations: m = rot.as_Euler_angles() o = backward(forward(m)) u = np.array([np.pi*2,np.pi,np.pi*2]) ok = np.allclose(m,o,atol=atol) ok |= np.allclose(np.where(np.isclose(m,u),m-u,m),np.where(np.isclose(o,u),o-u,o),atol=atol) if np.isclose(m[1],0.0,atol=atol) or np.isclose(m[1],np.pi,atol=atol): sum_phi = np.unwrap([m[0]+m[2],o[0]+o[2]]) ok |= np.isclose(sum_phi[0],sum_phi[1],atol=atol) assert ok and (np.zeros(3)-1.e-9 <= o).all() \ and (o <= np.array([np.pi*2.,np.pi,np.pi*2.])+1.e-9).all(), f'{m},{o},{rot.as_quaternion()}' @pytest.mark.parametrize('forward,backward',[(Rotation._ax2qu,Rotation._qu2ax), (Rotation._ax2om,Rotation._om2ax), (Rotation._ax2eu,Rotation._eu2ax), (Rotation._ax2ro,Rotation._ro2ax), (Rotation._ax2ho,Rotation._ho2ax), (Rotation._ax2cu,Rotation._cu2ax)]) def test_axis_angle_internal(self,set_of_rotations,forward,backward): """Ensure invariance of conversion from axis angle angles pair and back.""" for rot in set_of_rotations: m = rot.as_axis_angle() o = backward(forward(m)) ok = np.allclose(m,o,atol=atol) if np.isclose(m[3],np.pi,atol=atol): ok |= np.allclose(m*np.array([-1.,-1.,-1.,1.]),o,atol=atol) assert ok and np.isclose(np.linalg.norm(o[:3]),1.0) and o[3]<=np.pi+1.e-9, f'{m},{o},{rot.as_quaternion()}' @pytest.mark.parametrize('forward,backward',[(Rotation._ro2qu,Rotation._qu2ro), (Rotation._ro2om,Rotation._om2ro), (Rotation._ro2eu,Rotation._eu2ro), (Rotation._ro2ax,Rotation._ax2ro), (Rotation._ro2ho,Rotation._ho2ro), (Rotation._ro2cu,Rotation._cu2ro)]) def test_Rodrigues_internal(self,set_of_rotations,forward,backward): """Ensure invariance of conversion from Rodrigues-Frank vector and back.""" cutoff = np.tan(np.pi*.5*(1.-1e-5)) for rot in set_of_rotations: m = rot.as_Rodrigues_vector() o = backward(forward(m)) ok = np.allclose(np.clip(m,None,cutoff),np.clip(o,None,cutoff),atol=atol) ok |= np.isclose(m[3],0.0,atol=atol) if m[3] > cutoff: ok |= np.allclose(m[:3],-1*o[:3]) assert ok and np.isclose(np.linalg.norm(o[:3]),1.0), f'{m},{o},{rot.as_quaternion()}' @pytest.mark.parametrize('forward,backward',[(Rotation._ho2qu,Rotation._qu2ho), (Rotation._ho2om,Rotation._om2ho), #(Rotation._ho2eu,Rotation._eu2ho), (Rotation._ho2ax,Rotation._ax2ho), (Rotation._ho2ro,Rotation._ro2ho), (Rotation._ho2cu,Rotation._cu2ho)]) def test_homochoric_internal(self,set_of_rotations,forward,backward): """Ensure invariance of conversion from homochoric vector and back.""" for rot in set_of_rotations: m = rot.as_homochoric() o = backward(forward(m)) ok = np.allclose(m,o,atol=atol) assert ok and np.linalg.norm(o) < _R1 + 1.e-9, f'{m},{o},{rot.as_quaternion()}' @pytest.mark.parametrize('forward,backward',[(Rotation._cu2qu,Rotation._qu2cu), (Rotation._cu2om,Rotation._om2cu), (Rotation._cu2eu,Rotation._eu2cu), (Rotation._cu2ax,Rotation._ax2cu), (Rotation._cu2ro,Rotation._ro2cu), (Rotation._cu2ho,Rotation._ho2cu)]) def test_cubochoric_internal(self,set_of_rotations,forward,backward): """Ensure invariance of conversion from cubochoric vector and back.""" for rot in set_of_rotations: m = rot.as_cubochoric() o = backward(forward(m)) ok = np.allclose(m,o,atol=atol) if np.count_nonzero(np.isclose(np.abs(o),np.pi**(2./3.)*.5)): ok |= np.allclose(m*-1.,o,atol=atol) assert ok and np.max(np.abs(o)) < np.pi**(2./3.) * 0.5 + 1.e-9, f'{m},{o},{rot.as_quaternion()}' @pytest.mark.parametrize('vectorized, single',[(Rotation._qu2om,qu2om), (Rotation._qu2eu,qu2eu), (Rotation._qu2ax,qu2ax), (Rotation._qu2ro,qu2ro), (Rotation._qu2ho,qu2ho)]) def test_quaternion_vectorization(self,set_of_quaternions,vectorized,single): """Check vectorized implementation for quaternion against single point calculation.""" qu = np.array(set_of_quaternions) vectorized(qu.reshape(qu.shape[0]//2,-1,4)) co = vectorized(qu) for q,c in zip(qu,co): assert np.allclose(single(q),c) and np.allclose(single(q),vectorized(q)), f'{q},{c}' @pytest.mark.parametrize('vectorized, single',[(Rotation._om2qu,om2qu), (Rotation._om2eu,om2eu), (Rotation._om2ax,om2ax)]) def test_matrix_vectorization(self,set_of_rotations,vectorized,single): """Check vectorized implementation for rotation matrix against single point calculation.""" om = np.array([rot.as_matrix() for rot in set_of_rotations]) vectorized(om.reshape(om.shape[0]//2,-1,3,3)) co = vectorized(om) for o,c in zip(om,co): assert np.allclose(single(o),c) and np.allclose(single(o),vectorized(o)), f'{o},{c}' @pytest.mark.parametrize('vectorized, single',[(Rotation._eu2qu,eu2qu), (Rotation._eu2om,eu2om), (Rotation._eu2ax,eu2ax), (Rotation._eu2ro,eu2ro)]) def test_Eulers_vectorization(self,set_of_rotations,vectorized,single): """Check vectorized implementation for Euler angles against single point calculation.""" eu = np.array([rot.as_Euler_angles() for rot in set_of_rotations]) vectorized(eu.reshape(eu.shape[0]//2,-1,3)) co = vectorized(eu) for e,c in zip(eu,co): assert np.allclose(single(e),c) and np.allclose(single(e),vectorized(e)), f'{e},{c}' @pytest.mark.parametrize('vectorized, single',[(Rotation._ax2qu,ax2qu), (Rotation._ax2om,ax2om), (Rotation._ax2ro,ax2ro), (Rotation._ax2ho,ax2ho)]) def test_axis_angle_vectorization(self,set_of_rotations,vectorized,single): """Check vectorized implementation for axis angle pair against single point calculation.""" ax = np.array([rot.as_axis_angle() for rot in set_of_rotations]) vectorized(ax.reshape(ax.shape[0]//2,-1,4)) co = vectorized(ax) for a,c in zip(ax,co): assert np.allclose(single(a),c) and np.allclose(single(a),vectorized(a)), f'{a},{c}' @pytest.mark.parametrize('vectorized, single',[(Rotation._ro2ax,ro2ax), (Rotation._ro2ho,ro2ho)]) def test_Rodrigues_vectorization(self,set_of_rotations,vectorized,single): """Check vectorized implementation for Rodrigues-Frank vector against single point calculation.""" ro = np.array([rot.as_Rodrigues_vector() for rot in set_of_rotations]) vectorized(ro.reshape(ro.shape[0]//2,-1,4)) co = vectorized(ro) for r,c in zip(ro,co): assert np.allclose(single(r),c) and np.allclose(single(r),vectorized(r)), f'{r},{c}' @pytest.mark.parametrize('vectorized, single',[(Rotation._ho2ax,ho2ax), (Rotation._ho2cu,ho2cu)]) def test_homochoric_vectorization(self,set_of_rotations,vectorized,single): """Check vectorized implementation for homochoric vector against single point calculation.""" ho = np.array([rot.as_homochoric() for rot in set_of_rotations]) vectorized(ho.reshape(ho.shape[0]//2,-1,3)) co = vectorized(ho) for h,c in zip(ho,co): assert np.allclose(single(h),c) and np.allclose(single(h),vectorized(h)), f'{h},{c}' @pytest.mark.parametrize('vectorized, single',[(Rotation._cu2ho,cu2ho)]) def test_cubochoric_vectorization(self,set_of_rotations,vectorized,single): """Check vectorized implementation for cubochoric vector against single point calculation.""" cu = np.array([rot.as_cubochoric() for rot in set_of_rotations]) vectorized(cu.reshape(cu.shape[0]//2,-1,3)) co = vectorized(cu) for u,c in zip(cu,co): assert np.allclose(single(u),c) and np.allclose(single(u),vectorized(u)), f'{u},{c}' @pytest.mark.parametrize('func',[Rotation.from_axis_angle]) def test_normalization_vectorization(self,func): """Check vectorized implementation normalization.""" vec = np.random.rand(5,4) ori = func(vec,normalize=True) for v,o in zip(vec,ori): assert np.allclose(func(v,normalize=True).as_quaternion(),o.as_quaternion()) def test_invalid_init(self): with pytest.raises(TypeError): Rotation(np.ones(3)) def test_to_numpy(self): r = Rotation.from_random(np.random.randint(0,10,4)) assert (r.as_quaternion() == np.array(r)).all() def test_bounds(self,multidim_rotations): m = multidim_rotations q = m.as_quaternion() assert np.allclose(1.,np.linalg.norm(q,axis=-1)) v = m.as_Rodrigues_vector(compact=False) assert np.allclose(1.,np.linalg.norm(v[...,:3],axis=-1)) v = m.as_axis_angle(degrees=False) assert np.allclose(1.,np.linalg.norm(v[...,:3],axis=-1)) assert (v[...,3] >= 0.).all and (v < np.pi+1.e-9).all() r = m.as_matrix() assert np.allclose(1.,np.linalg.det(r)) e = m.as_Euler_angles(degrees=False) assert (e >= 0.).all and (e < np.pi*np.array([2.,1.,2.])+1.e-9).all() c = m.as_cubochoric() assert (np.linalg.norm(c,ord=np.inf,axis=-1) < np.pi**(2./3.)*0.5+1.e-9).all() h = m.as_homochoric() assert (np.linalg.norm(h,axis=-1) < (3.*np.pi/4.)**(1./3.) + 1.e-9).all() @pytest.mark.parametrize('accept_homomorph',[True,False]) @pytest.mark.parametrize('normalize',[True,False]) @pytest.mark.parametrize('P',[1,-1]) def test_quaternion(self,multidim_rotations,accept_homomorph,normalize,P): c = np.array([1,-P,-P,-P]) * (-1 if accept_homomorph else 1) * (0.9 if normalize else 1.0) m = multidim_rotations o = Rotation.from_quaternion(m.as_quaternion()*c, accept_homomorph=accept_homomorph, normalize=normalize, P=P) f = Rotation(np.where(np.isclose(m.as_quaternion()[...,0],0.0,atol=atol)[...,np.newaxis],~o,o)) assert np.logical_or(m.isclose(o,atol=atol), m.isclose(f,atol=atol) ).all() @pytest.mark.parametrize('degrees',[True,False]) def test_Eulers(self,multidim_rotations,degrees): m = multidim_rotations o = Rotation.from_Euler_angles(m.as_Euler_angles(degrees), degrees=degrees) f = Rotation(np.where(np.isclose(m.as_quaternion()[...,0],0.0,atol=atol)[...,np.newaxis],~o,o)) assert np.logical_or(m.isclose(o,atol=atol), m.isclose(f,atol=atol) ).all() @pytest.mark.parametrize('degrees',[True,False]) @pytest.mark.parametrize('normalize',[True,False]) @pytest.mark.parametrize('P',[1,-1]) def test_axis_angle(self,multidim_rotations,degrees,normalize,P): c = np.array([-P,-P,-P,1.]) c[:3] *= 0.9 if normalize else 1.0 m = multidim_rotations o = Rotation.from_axis_angle(m.as_axis_angle(degrees)*c, degrees=degrees, normalize=normalize, P=P) f = Rotation(np.where(np.isclose(m.as_quaternion()[...,0],0.0,atol=atol)[...,np.newaxis],~o,o)) assert np.logical_or(m.isclose(o,atol=atol), m.isclose(f,atol=atol) ).all() @pytest.mark.parametrize('normalize',[True,False]) def test_matrix(self,multidim_rotations,normalize): m = multidim_rotations o = Rotation.from_matrix(m.as_matrix()*(0.9 if normalize else 1.0), normalize=normalize) f = Rotation(np.where(np.isclose(m.as_quaternion()[...,0],0.0,atol=atol)[...,np.newaxis],~o,o)) assert np.logical_or(m.isclose(o,atol=atol), m.isclose(f,atol=atol) ).all() def test_parallel(self,multidim_rotations): m = multidim_rotations a = np.broadcast_to(np.array([[1.0,0.0,0.0], [0.0,1.0,0.0]]),m.shape+(2,3)) assert m.allclose(Rotation.from_parallel(a,m.broadcast_to(m.shape+(2,))@a)) @pytest.mark.parametrize('normalize',[True,False]) @pytest.mark.parametrize('P',[1,-1]) def test_Rodrigues(self,multidim_rotations,normalize,P): c = np.array([-P,-P,-P,1.]) c[:3] *= 0.9 if normalize else 1.0 m = multidim_rotations o = Rotation.from_Rodrigues_vector(m.as_Rodrigues_vector()*c, normalize=normalize, P=P) f = Rotation(np.where(np.isclose(m.as_quaternion()[...,0],0.0,atol=atol)[...,np.newaxis],~o,o)) assert np.logical_or(m.isclose(o,atol=atol), m.isclose(f,atol=atol) ).all() def test_Rodrigues_compact(self,multidim_rotations): m = multidim_rotations c = m.as_Rodrigues_vector(compact=True) r = m.as_Rodrigues_vector(compact=False) assert np.allclose(r[...,:3]*r[...,3:], c, equal_nan=True) @pytest.mark.parametrize('P',[1,-1]) def test_homochoric(self,multidim_rotations,P): m = multidim_rotations o = Rotation.from_homochoric(m.as_homochoric()*-P, P=P) f = Rotation(np.where(np.isclose(m.as_quaternion()[...,0],0.0,atol=atol)[...,np.newaxis],~o,o)) assert np.logical_or(m.isclose(o,atol=atol), m.isclose(f,atol=atol) ).all() @pytest.mark.parametrize('P',[1,-1]) def test_cubochoric(self,multidim_rotations,P): m = multidim_rotations o = Rotation.from_cubochoric(m.as_cubochoric()*-P, P=P) f = Rotation(np.where(np.isclose(m.as_quaternion()[...,0],0.0,atol=atol)[...,np.newaxis],~o,o)) assert np.logical_or(m.isclose(o,atol=atol), m.isclose(f,atol=atol) ).all() @pytest.mark.parametrize('reciprocal',[True,False]) def test_basis(self,multidim_rotations,reciprocal): m = multidim_rotations r = m.as_matrix() r = np.linalg.inv(tensor.transpose(r)/np.pi) if reciprocal else r o = Rotation.from_basis(r, reciprocal=reciprocal) f = Rotation(np.where(np.isclose(m.as_quaternion()[...,0],0.0,atol=atol)[...,np.newaxis],~o,o)) assert np.logical_or(m.isclose(o,atol=atol), m.isclose(f,atol=atol) ).all() @pytest.mark.parametrize('shape',[None,1,(4,4)]) def test_random(self,shape): r = Rotation.from_random(shape) assert r.shape == () if shape is None else (1,) if shape == 1 else shape @pytest.mark.parametrize('shape',[None,5,(4,6)]) def test_equal(self,shape): R = Rotation.from_random(shape,rng_seed=1) assert R == R if shape is None else (R == R).all() @pytest.mark.parametrize('shape',[None,5,(4,6)]) def test_allclose(self,shape): R = Rotation.from_random(shape,rng_seed=1) assert R.allclose(R) @pytest.mark.parametrize('shape',[None,5,(4,6)]) def test_unequal(self,shape): R = Rotation.from_random(shape,rng_seed=1) assert not (R != R if shape is None else (R != R).any()) def test_equal_ambiguous(self): qu = np.random.rand(10,4) qu[:,0] = 0. qu /= np.linalg.norm(qu,axis=1,keepdims=True) assert (Rotation(qu) == Rotation(-qu)).all() def test_inversion(self): r = Rotation.from_random() assert r == ~~r @pytest.mark.parametrize('shape',[1,(1,),(4,2),(1,1,1),tuple(np.random.randint(0,10,4))]) def test_size(self,shape): assert Rotation.from_random(shape).size == np.prod(shape) @pytest.mark.parametrize('shape',[None,1,(1,),(4,2),(1,1,1),tuple(np.random.randint(0,10,4))]) def test_shape(self,shape): r = Rotation.from_random(shape=shape) assert r.shape == (shape if isinstance(shape,tuple) else (shape,) if shape else ()) @pytest.mark.parametrize('shape',[None,1,(1,),(4,2),(3,3,2)]) def test_append(self,shape): r = Rotation.from_random(shape=shape) p = Rotation.from_random(shape=shape) s = r.append(p) print(f'append 2x {shape} --> {s.shape}') assert np.logical_and(s[0,...] == r[0,...], s[-1,...] == p[-1,...]).all() @pytest.mark.parametrize('shape',[None,1,(1,),(4,2),(3,3,2)]) def test_append_list(self,shape): r = Rotation.from_random(shape=shape) p = Rotation.from_random(shape=shape) s = r.append([r,p]) print(f'append 3x {shape} --> {s.shape}') assert np.logical_and(s[0,...] == r[0,...], s[-1,...] == p[-1,...]).all() @pytest.mark.parametrize('quat,standardized',[ ([-1,0,0,0],[1,0,0,0]), ([-0.5,-0.5,-0.5,-0.5],[0.5,0.5,0.5,0.5]), ]) def test_standardization(self,quat,standardized): assert Rotation(quat)._standardize() == Rotation(standardized) @pytest.mark.parametrize('shape,length',[ ((2,3,4),2), (4,4), ((),0) ]) def test_len(self,shape,length): r = Rotation.from_random(shape=shape) assert len(r) == length @pytest.mark.parametrize('shape',[(4,6),(2,3,4),(3,3,3)]) @pytest.mark.parametrize('order',['C','F']) def test_flatten_reshape(self,shape,order): r = Rotation.from_random(shape=shape) assert (r == r.flatten(order).reshape(shape,order)).all() @pytest.mark.parametrize('function',[Rotation.from_quaternion, Rotation.from_Euler_angles, Rotation.from_axis_angle, Rotation.from_matrix, Rotation.from_Rodrigues_vector, Rotation.from_homochoric, Rotation.from_cubochoric]) def test_invalid_shape(self,function): invalid_shape = np.random.random(np.random.randint(8,32,(3))) with pytest.raises(ValueError): function(invalid_shape) def test_invalid_shape_parallel(self): invalid_a = np.random.random(np.random.randint(8,32,(3))) invalid_b = np.random.random(np.random.randint(8,32,(3))) with pytest.raises(ValueError): Rotation.from_parallel(invalid_a,invalid_b) @pytest.mark.parametrize('fr,to',[(Rotation.from_quaternion,'as_quaternion'), (Rotation.from_axis_angle,'as_axis_angle'), (Rotation.from_Rodrigues_vector, 'as_Rodrigues_vector'), (Rotation.from_homochoric,'as_homochoric'), (Rotation.from_cubochoric,'as_cubochoric')]) def test_invalid_P(self,fr,to): R = Rotation.from_random(np.random.randint(8,32,(3))) # noqa with pytest.raises(ValueError): fr(eval(f'R.{to}()'),P=-30) def test_invalid_multiplication(self): rot = Rotation.from_random() with pytest.raises(TypeError): rot@Rotation.from_random() with pytest.raises(TypeError): rot@[1,2,3,4] @pytest.mark.parametrize('shape',[None,(3,),(4,2)]) def test_broadcast(self,shape): rot = Rotation.from_random(shape) new_shape = tuple(np.random.randint(8,32,(3))) if shape is None else \ rot.shape + (np.random.randint(8,32),) rot_broadcast = rot.broadcast_to(tuple(new_shape)) for i in range(rot_broadcast.shape[-1]): assert np.allclose(rot_broadcast.quaternion[...,i,:], rot.quaternion) @pytest.mark.parametrize('shape',[(3,2),(4,6)]) def test_broadcastcomposition(self,shape): a = Rotation.from_random(shape[0]) b = Rotation.from_random(shape[1]) assert (a[:,np.newaxis]*b[np.newaxis,:]).allclose(a.broadcast_to(shape)*b.broadcast_to(shape)) @pytest.mark.parametrize('function,invalid',[(Rotation.from_quaternion, np.array([-1,0,0,0])), (Rotation.from_quaternion, np.array([1,1,1,0])), (Rotation.from_Euler_angles, np.array([1,4,0])), (Rotation.from_Euler_angles, np.array([-1,0,0])), (Rotation.from_axis_angle, np.array([1,0,0,4])), (Rotation.from_axis_angle, np.array([1,1,0,1])), (Rotation.from_matrix, np.random.rand(3,3)), (Rotation.from_matrix, np.array([[1,1,0],[1,2,0],[0,0,1]])), (Rotation.from_Rodrigues_vector, np.array([1,0,0,-1])), (Rotation.from_Rodrigues_vector, np.array([1,1,0,1])), (Rotation.from_homochoric, np.array([2,2,2])), (Rotation.from_cubochoric, np.array([1.1,0,0])), ]) def test_invalid_value(self,function,invalid): with pytest.raises(ValueError): function(invalid) @pytest.mark.parametrize('direction',['forward', 'backward']) def test_pyramid_vectorization(self,direction): p = np.random.rand(n,3) o = Rotation._get_pyramid_order(p,direction) for i,o_i in enumerate(o): assert (o_i==Rotation._get_pyramid_order(p[i],direction)).all() def test_pyramid_invariant(self): a = np.random.rand(n,3) f = Rotation._get_pyramid_order(a,'forward') b = Rotation._get_pyramid_order(a,'backward') assert (np.take_along_axis(np.take_along_axis(a,f,-1),b,-1) == a).all() @pytest.mark.parametrize('data',[np.random.rand(5,3), np.random.rand(5,3,3), np.random.rand(5,3,3,3,3)]) def test_rotate_vectorization(self,set_of_rotations,data): for rot in set_of_rotations: v = rot.broadcast_to((5,)) @ data for i in range(data.shape[0]): assert np.allclose(mul(rot,data[i]),v[i]), f'{i-data[i]}' @pytest.mark.parametrize('data',[np.random.rand(3), np.random.rand(3,3), np.random.rand(3,3,3,3)]) def test_rotate_identity(self,data): R = Rotation() print(R,data) assert np.allclose(data,R@data) @pytest.mark.parametrize('data',[np.random.rand(3), np.random.rand(3,3), np.random.rand(3,3,3,3)]) def test_rotate_360deg(self,data): phi_1 = np.random.random() * np.pi phi_2 = 2*np.pi - phi_1 R_1 = Rotation.from_Euler_angles(np.array([phi_1,0.,0.])) R_2 = Rotation.from_Euler_angles(np.array([0.,0.,phi_2])) assert np.allclose(data,R_2@(R_1@data)) @pytest.mark.parametrize('pwr',[-10,0,1,2.5,np.pi,np.random.random()]) def test_rotate_power(self,pwr): R = Rotation.from_random() axis_angle = R.as_axis_angle() axis_angle[ 3] = (pwr*axis_angle[-1])%(2.*np.pi) if axis_angle[3] > np.pi: axis_angle[3] -= 2.*np.pi axis_angle *= -1 assert (R**pwr).isclose(Rotation.from_axis_angle(axis_angle)) def test_rotate_inverse(self): R = Rotation.from_random() assert np.allclose(np.eye(3),(~R*R).as_matrix()) @pytest.mark.parametrize('data',[np.random.rand(3), np.random.rand(3,3), np.random.rand(3,3,3,3)]) def test_rotate_inverse_array(self,data): R = Rotation.from_random() assert np.allclose(data,~R@(R@data)) @pytest.mark.parametrize('data',[np.random.rand(4), np.random.rand(3,2), np.random.rand(3,3,3,1)]) def test_rotate_invalid_shape(self,data): R = Rotation.from_random() with pytest.raises(ValueError): R@data @pytest.mark.parametrize('data',['does_not_work', (1,2), 5]) def test_rotate_invalid_type(self,data): R = Rotation.from_random() with pytest.raises(TypeError): R@data def test_misorientation_invariant(self): R = Rotation.from_random() assert np.allclose(R.misorientation(R).as_matrix(),np.eye(3)) def test_misorientation_average(self): """2 times the average is the misorientation.""" r = Rotation.from_random(2) a = r[0].misorientation(r[1]).as_axis_angle() b = r.average().misorientation(r[1]).as_axis_angle() b[3] = (b[3]*2)%np.pi assert np.allclose(a,b) def test_misorientation_360deg(self): R_1 = Rotation() R_2 = Rotation.from_Euler_angles([360,0,0],degrees=True) assert np.allclose(R_1.misorientation(R_2).as_matrix(),np.eye(3)) def test_composition(self): a,b = (Rotation.from_random(),Rotation.from_random()) c = a * b a *= b assert c == a def test_composition_invalid(self): with pytest.raises(TypeError): Rotation()*np.ones(3) def test_composition_inverse(self): a,b = (Rotation.from_random(),Rotation.from_random()) c = a / b a /= b assert c == a def test_composition_inverse_invalid(self): with pytest.raises(TypeError): Rotation()/np.ones(3) def test_power(self): a = Rotation.from_random() r = (np.random.rand()-.5)*4 b = a**r a **= r assert a == b def test_invariant(self): R = Rotation.from_random() assert (R/R).isclose(R*R**(-1)) and (R/R).isclose(Rotation()) @pytest.mark.parametrize('item',[np.ones(3),np.ones((3,3)), np.ones((3,3,3,3))]) def test_apply(self,item): r = Rotation.from_random() assert (r.apply(item) == r@item).all() @pytest.mark.parametrize('angle',[10,20,30,40,50,60,70,80,90,100,120]) def test_average(self,angle): R = Rotation.from_axis_angle([[0,0,1,10],[0,0,1,angle]],degrees=True) avg_angle = R.average().as_axis_angle(degrees=True,pair=True)[1] assert np.isclose(avg_angle,10+(angle-10)/2.) @pytest.mark.parametrize('sigma',[5,10,15,20]) @pytest.mark.parametrize('shape',[1000,10000,100000,(10,100)]) def test_spherical_component(self,sigma,shape): p = [] for run in range(5): c = Rotation.from_random() o = Rotation.from_spherical_component(c,sigma,shape,degrees=True) _, angles = c.misorientation(o).as_axis_angle(pair=True,degrees=True) angles[::2] *= -1 # flip angle for every second to symmetrize distribution p.append(stats.normaltest(angles)[1]) sigma_out = np.std(angles) p = np.average(p) assert (.9 < sigma/sigma_out < 1.1) and p > 1e-2, f'{sigma/sigma_out},{p}' @pytest.mark.parametrize('sigma',[5,10,15,20]) @pytest.mark.parametrize('shape',[1000,10000,100000,(10,100)]) def test_from_fiber_component(self,sigma,shape): def astuple(a): return tuple(a) if hasattr(a,'__len__') else (a,) p = [] for run in range(9): alpha = np.arccos(np.random.random()),np.random.random()*2*np.pi beta = np.arccos(np.random.random()),np.random.random()*2*np.pi f_in_C = np.array([np.sin(alpha[0])*np.cos(alpha[1]), np.sin(alpha[0])*np.sin(alpha[1]), np.cos(alpha[0])]) f_in_S = np.array([np.sin( beta[0])*np.cos( beta[1]), np.sin( beta[0])*np.sin( beta[1]), np.cos( beta[0])]) ax = np.append(np.cross(f_in_C,f_in_S), - np.arccos(np.dot(f_in_C,f_in_S))) n = Rotation.from_axis_angle(ax if ax[3] > 0.0 else -ax,normalize=True) # rotation to align fiber axis in crystal and sample system o = Rotation.from_fiber_component(alpha,beta,np.radians(sigma),shape,False) angles = np.arccos(np.clip(np.dot(o@np.broadcast_to(f_in_S,astuple(shape)+(3,)),n@f_in_S),-1,1)) dist = np.array(angles) * (np.random.randint(0,2,shape)*2-1) p.append(stats.normaltest(dist)[1]) sigma_out = np.degrees(np.std(dist)) p = np.average(p) assert (.9 < sigma/sigma_out < 1.1) and p > 1e-2, f'{sigma/sigma_out},{p}' @pytest.mark.parametrize('fractions',[True,False]) @pytest.mark.parametrize('degrees',[True,False]) @pytest.mark.parametrize('shape',[2**13,2**14,2**15,(2**8,2**6)]) def test_ODF_cell(self,res_path,fractions,degrees,shape): steps = np.array([144,36,36]) limits = np.array([360.,90.,90.]) rng = tuple(zip(np.zeros(3),limits)) weights = Table.load(res_path/'ODF_experimental_cell.txt').get('intensity').flatten() Eulers = grid_filters.coordinates0_point(steps,limits) Eulers = np.radians(Eulers) if not degrees else Eulers Eulers_r = Rotation.from_ODF(weights,Eulers.reshape(-1,3,order='F'),shape,degrees,fractions).as_Euler_angles(True) weights_r = np.histogramdd(Eulers_r.reshape(-1,3),steps,rng)[0].flatten(order='F')/np.prod(shape) * np.sum(weights) if fractions: assert np.sqrt(((weights_r - weights) ** 2).mean()) < 4 @pytest.mark.parametrize('degrees',[True,False]) @pytest.mark.parametrize('shape',[2**13,2**14,2**15,(2**8,2**6)]) def test_ODF_node(self,res_path,degrees,shape): steps = np.array([144,36,36]) limits = np.array([360.,90.,90.]) rng = tuple(zip(-limits/steps*.5,limits-limits/steps*.5)) weights = Table.load(res_path/'ODF_experimental.txt').get('intensity') weights = weights.reshape(steps+1,order='F')[:-1,:-1,:-1].reshape(-1,order='F') Eulers = grid_filters.coordinates0_node(steps,limits)[:-1,:-1,:-1] Eulers = np.radians(Eulers) if not degrees else Eulers Eulers_r = Rotation.from_ODF(weights,Eulers.reshape(-1,3,order='F'),shape,degrees).as_Euler_angles(True) weights_r = np.histogramdd(Eulers_r.reshape(-1,3),steps,rng)[0].flatten(order='F')/np.prod(shape) * np.sum(weights) assert np.sqrt(((weights_r - weights) ** 2).mean()) < 5 def test_mul_invalid(self): with pytest.raises(TypeError): Rotation.from_random()*np.ones(3)